西藏地区潜在蒸散量变化特征及灰色模型预测初探

doi:10.12118/j.issn.1000–6060.2021.06.06

摘要/Abstract

摘要：

基于西藏地区38个气象站点1981—2019年逐日气象资料,采用Penman-Monteith模型、趋势分析、Morlet小波分析、Mann-Kendall检验、经验正交函数法（Empirical orthogonal function,EOF）和灰色模型探究潜在蒸散量（ET₀）的时空演变规律以及未来ET₀的变化趋势。结果表明：在时间尺度上,西藏地区ET₀平均为597.12 mm,1981—2001年呈显著的减少趋势、2002—2019年呈显著的增加趋势（P<0.01）;西藏全区及五大气候区年均ET₀均呈现增加趋势（除东南部）,且均以33 a的周期震荡为第一主周期。在空间尺度上,年ET₀主要呈现由中部中心向西南和东南逐步递减的分布特征,高值中心集中在沿江一线,低值中心位于南部地区。年ET₀发生突变的站点主要分布在南部边缘地区、沿江一线和东北部,发生时间集中在20世纪80年代。构建的GM（1, 1）预测模型预测精度均值为87.85%,可用于西藏年均ET₀日期序列的中长期预测,预测结果显示,除东南部年ET₀的预测值有明显下降,其他区域均呈现上升态势。

关键词: Penman-Monteith模型, 潜在蒸散量, 时空分析, 灰色模型, 西藏

Abstract:

This paper aims to provide a scientific basis for water-saving irrigation, the rational allocation of water resources, and drought monitoring in Tibet, China. We use the Penman-Monteith model, trend analysis, Morlet wavelet analysis, Mann-Kendall tests, the empirical orthogonal function, and gray models to explore the spatiotemporal evolution of potential evapotranspiration (ET₀) in Tibet and the central and western regions of Nagqu as well as the trend of future ET₀ changes based on daily meteorological data collected from 1981 to 2019 at 38 meteorological stations in the region. The results demonstrate that on the time scale, the average ET₀ in Tibet is 597.12 mm. It also exhibited a significant decreasing trend from 1981 to 2001 and a significant increasing trend from 2002 to 2019 (P<0.01). In these two distinct time periods, high evapotranspiration was concentrated in the central and western areas of Nagqu and along the river line. In the first mode (EOF1), the annual ET₀ change trend in Tibet had a high degree of consistency in space, mainly exhibiting a gradually decreasing distribution from the center of the central area to the southwest and southeast. The high-value center is concentrated along the river line, and the low-value center was located in the southern region. Concerning space, the positive center of central and western Tibet and the negative center of southeastern Tibet are reversed. The stations with positive Kendall trend coefficients are mainly concentrated in the central and western regions of Nagqu and the southern marginal area, where the climate has been warming and drying. The sites exhibiting abrupt changes in annual ET₀ are mainly distributed in the southern marginal area along the river line and the northeast and were concentrated in time. In the 1980s, two mutations occurred in the potential evapotranspiration at Nagqu and Dangxiong stations, whereas one or no mutations occurred at each of the remaining stations. The annual average ET₀ both of Tibet as a whole and of the five major climate zones exhibited an increasing trend (except in the southeast), and the 33 year cyclic oscillation was the first main cycle. Additionally, there was a cycle of 11 a in the whole region and along the river line. The midwest of Nagqu had cycles of 22 a and 3 a, the southern marginal area had cycles of 8 a and 12 a, the northeast had a cycle of 8 a, and the southeast had main cycles of 22 a and 12 a. The constructed gray model (GM; 1, 1) used for prediction had gray parameters a≥-0.3 and a∈(-2, 2), and the level ratio was in a smooth state, meaning it can be used to predict future ET₀. The average prediction accuracy was 87.85%, so we predicted the medium- and long-term average annual ET₀ date series for Tibet. The forecast results revealed that except for the significant decline in the forecast value of the annual ET₀ in the southeast, all other regions are exhibiting an upward trend, and the southern edge shows the steepest increase.

Key words: Penman-Monteith model, evapotranspiration, spatiotemporal analysis, grey model, Tibet

史继清,边多,杨霏云,甘臣龙,樊栋樑. 西藏地区潜在蒸散量变化特征及灰色模型预测初探[J]. 干旱区地理, 2021, 44(6): 1570-1579.

SHI Jiqing,BIAN Duo,YANG Feiyun,GAN Chenlong,FAN Dongliang. Variation characteristics of potential evapotranspiration and the forecast of grey model in Tibet[J]. Arid Land Geography, 2021, 44(6): 1570-1579.

图/表 6

图1

图2

图3

图4

图5

表1

各站点GM（1, 1）模型的参数和检验结果"

气候区	站点	模型中的参数		预测精度/%	$级比 σ 0$	气候区	站点	模型中的参数		预测精度/%	$级比 σ 0$
气候区	站点	a	u	预测精度/%	$级比 σ 0$	气候区	站点	a	u	预测精度/%	$级比 σ 0$
那曲中西部	那曲	-0.0036	424.38	86.55	0.61~1.66	南部边缘地区	聂拉木	-0.0076	421.78	91.60	0.78~1.21
	班戈	-0.0016	657.56	89.71	0.62~1.51		定日	-0.0025	670.98	88.46	0.80~1.31
	申扎	0.0012	710.82	87.12	0.65~1.32		隆子	0.0037	752.32	93.24	0.80~1.19
	当雄	-0.0043	443.73	81.01	0.58~1.63		错那	-0.0064	258.23	89.19	0.76~1.31
	安多	0.0008	508.92	87.29	0.65~1.44		帕里	-0.0071	310.47	88.95	0.63~1.27
	狮泉河	-0.0061	740.05	91.36	0.77~1.24	东南部	林芝	-0.0006	483.09	87.46	0.65~1.82
	普兰	-0.0011	784.19	94.75	0.80~1.18		波密	-0.0034	353.26	87.46	0.77~1.35
	改则	0.0003	862.05	92.26	0.78~1.37		察隅	0.0002	575.12	81.51	0.74~1.52
沿江一线	拉萨	-0.0079	693.78	90.42	0.46~1.62		左贡	-0.0031	403.29	86.99	0.74~1.78
	泽当	0.0047	1001.80	87.58	0.57~1.78		芒康	0.0007	467.01	85.04	0.66~1.27
	日喀则	-0.0105	526.21	85.61	0.70~1.40		米林	-0.0034	327.10	90.58	0.79~1.31
	江孜	0.0009	688.26	86.10	0.68~1.28		八宿	0.0073	1227.70	89.23	0.53~1.42
	浪卡子	-0.0009	592.48	90.30	0.70~1.34	东北部	昌都	-0.0148	349.23	74.83	0.62~1.42
	拉孜	-0.0003	884.31	79.57	0.46~1.62		丁青	-0.0055	321.21	79.52	0.68~1.84
	尼木	-0.0060	514.40	63.90	0.60~1.87		索县	-0.0083	369.50	80.44	0.64~1.68
	贡嘎	0.0113	924.95	88.36	0.56~1.35		嘉黎	-0.0038	298.42	87.83	0.73~1.39
	墨竹工卡	-0.0012	792.12	88.23	0.71~1.32		比如	0.0059	427.13	83.81	0.66~1.21
	加查	-0.0012	634.69	89.50	0.73~1.43		洛隆	0.0022	732.76	88.66	0.66~1.36
	南木林	0.0063	678.85	59.13	0.44~1.44		类乌齐	0.0019	375.38	85.66	0.62~1.57

表1

参考文献 34

[1]	曹永强, 肖春柳, 李元菲. 河北省春季潜在蒸散量变化特征与成因[J]. 水土保持研究, 2019, 26(5):195-209.
	[ Cao Yongqiang, Xiao Chunliu, Li Yuanfei. Charcteristics and causes of potential evapotranspiration in spring in Hebei Province[J]. Research of Soil and Water Conservation, 2019, 26(5):195-209. ]
[2]	徐宗学. 水文模型[M]. 北京: 科学出版社, 2009.
	[ Xu Zongxue. Hydrological modelling[M]. Beijing: Meteorological Press, 2009. ]
[3]	Brutsaert W, Parlange M B. Hydrologic cycle explains the evaporation paradox[J]. Nature, 1998, 396(6706):30. doi: 10.1038/23845
[4]	张璐, 朱仲元, 张圣微, 等. 近59 a锡林河流域潜在蒸散发及地表干湿状况变化趋势分析[J]. 干旱区地理, 2020, 43(4):997-1003.
	[ Zhang Lu, Zhu Zhongyuan, Zhang Shengwei, et al. Trends of potential evapotranspiration and surface wet conditions in the Xilin River Basin in recent 59 years[J]. Arid Land Geography, 2020, 43(4):997-1003.
[5]	赵志平, 吴晓莆, 李果, 等. 2009—2011年我国西南地区旱灾程度及其对植被净初级生产力的影响[J]. 生态学报, 2015, 35(2):350-360.
	[ Zhao Zhiping, Wu Xiaofu, Li Guo, et al. Drought severity and its impact on vegetation net primary productivity in southwest China from 2009 to 2011[J]. Acta Ecologica Sinica, 2015, 35(2):350-360. ]
[6]	秦鹏程, 刘敏, 刘志雄, 等. 湖北省潜在蒸散估算模型对比[J]. 干旱气象, 2014, 32(3):334-339.
	[ Qin Pengcheng, Liu Min, Liu Zhixiong, et al. Comparison of potential evapotranspiration estimation models in Hubei Province[J]. Journal of Arid Meteorology, 2014, 32(3):334-339. ]
[7]	穆文彬, 孙素艳, 马伟希, 等. 若尔盖湿地潜在蒸散量演变特征及影响因素分析[J]. 高原气象, 2019, 38(4):716-724.
	[ Mu Wenbin, Sun Suyan, Ma Weixi, et al. Analysis on evolution characteristics and influencing factors on evapotranspiration of Zoige wetland[J]. Plateau Meteorology, 2019, 38(4):716-724. ]
[8]	Wilber L Q, Ricardo Z B, Pedro , et al. Can artificial neural networks estimate potential evapotranspiration in Peruvian highlands?[J]. Modeling Earth Systems and Environment, 2019, 5(4):1911-1924. doi: 10.1007/s40808-019-00647-2
[9]	拉巴, 除多, 德吉央宗. 基于SEBS 模型的藏北那曲蒸散量研究[J]. 遥感技术与应用, 2012, 27(6):919-926.
	[ La Ba, Chu Duo, Deji Yangzong. Study on evapotranspiration in northern Tibet based on SEBS model[J]. Remote Sensing Technology and Application, 2012, 27(6):919-926. ]
[10]	钟巧, 焦黎, 李稚, 等. 博斯腾湖流域潜在蒸散发时空演变及归因分析[J]. 干旱区地理, 2019, 42(1):103-112.
	[ Zhong Qiao, Jiao Li, Li Zhi, et al. Spatial and temporal changes of potential evapotranspiration and its attribution in the Bosten Lake Basin[J]. Arid Land Geography, 2019, 42(1):103-112. ]
[11]	Allen R G, Pereira L S, Raes D, et al. Crop evapotranspiration: Guidelines for computing crop water requirements[R]. FAO Irrigation and Drainage Pape 56, Rome, 1998.
[12]	Song X Y, Lu F, Xiao W H, et al. Performance of 12 reference evapotranspiration estimation methods compared with the Penman-Monteith method and the potential influences in northeast China[J]. Meteorological Applications, 2019, 26(1):83-96. doi: 10.1002/met.2019.26.issue-1
[13]	Yang Y, Chen R S, Song Y X, et al. Sensitivity of potential evapotranspiration to meteorological factors and their elevational gradients in the Qilian Mountains, northwestern China[J]. Journal of Hydrology, 2019, 568:147-159. doi: 10.1016/j.jhydrol.2018.10.069
[14]	Zhao Y F, Zou X Q, Cao L G, et al. Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over southwest China during 1960—2013[J]. Theoretical and Applied Climatology, 2018, 133(3-4):711-726. doi: 10.1007/s00704-017-2216-4
[15]	杜军, 边多, 拉巴, 等. 1971—2005年西藏主要农区农田蒸散量变化特征及其与环境因子的关系[J]. 冰川冻土, 2009, 31(5):815-821.
	[ Du Jun, Bian Duo, La Ba, et al. Changes in evapotranspiration in the main agriculture areas of central Tibet and its relation to the environment factors in 1971—2005[J]. Journal of Glaciology and Geocryology, 2009, 31(5):815-821. ]
[16]	杨永红, 张展羽, 阮新建. 西藏参考作物蒸发蒸腾量的时空变异规律[J]. 水科学进展, 2009, 20(6):775-781.
	[ Yang Yonghong, Zhang Zhanyu, Ruan Xinjian. Spatiotemporal variation of reference evapotranspiration in Tibet[J]. Advances in Water Science, 2009, 20(6):775-781. ]
[17]	毛飞, 卢志光, 张佳华, 等. 近40年那曲地区气候特征分析[J]. 高原气象, 2007, 26(4):708-715.
	[ Mao Fei, Lu Zhiguang, Zhang Jiahua, et al. Analysis on climate characteristics in Naqu in recent 40 years[J]. Plateau Meteorology, 2007, 26(4):708-715. ]
[18]	何慧根, 胡泽勇, 荀学义, 等. 藏北高原季节性冻土区潜在蒸散和干湿状况分析[J]. 高原气象, 2010, 29(1):10-16.
	[ He Huigen, Hu Zeyong, Xun Xueyi, et al. Analysis on potential evaptranspiration and dry-wet conditions in seasonal frozen soil region of northern Tibetan Plateau[J]. Plateau Meteorology, 2010, 29(1):10-16. ]
[19]	张娜, 金建新, 佟长福, 等. 西藏参考作物蒸散量时空变化特征与影响因素[J]. 干旱区研究, 2017, 34(5):1027-1034.
	[ Zhang Na, Jin Jianxin, Tong Changfu, et al. Spatiotemporal variation of evapotranspiration of referred crops and the affecting factors in Tibet[J]. Arid Zone Research, 2017, 34(5):1027-1034. ]
[20]	唐小萍, 罗礼洪, 卓玛, 等. 气候变化对西藏雅鲁藏布江中游地区潜在蒸散量的影响分析[J]. 高原山地气象研究, 2011, 31(3):49-53.
	[ Tang Xiaoping, Luo Lihong, Zhuo Ma, et al. Impact analysis of climate change on potential evapotranspiration over midstream of Yarlung Zangbo River in Tibetan Plateau[J]. Plateau and Mountain Meteorology Research, 2011, 31(3):49-53. ]
[21]	温克刚, 刘光轩. 中国气象灾害大典(西藏卷)[M]. 北京: 气象出版社, 2007: 21-25.
	[ Wen Kegang, Liu Guangxuan. Encyclopedia of Chinese meteorological disasters (Tibet Volume)[M]. Beijing: Meteorological Press, 2007: 21-25. ]
[22]	甘臣龙. 基于作物生育期的潜在蒸散的时空演变特征及R/S分析[J]. 西藏科技, 2015(5):53-56, 59.
	[ Gan Chenlong. Spatiotemporal evolution characteristics and R/S analysis of potential evapotranspiration based on crop growth period[J]. Tibet Science and Technology, 2015(5):53-56, 59. ]
[23]	李红瑛, 薛羽, 曹二佳, 等. 近50年来乌兰察布市水分盈亏量时空变化特征[J]. 干旱区资源与环境, 2019, 33(12):145-151.
	[ Li Hongying, Xue Yu, Cao Erjia, et al. Spatiotemporal variation characteristics of waterdeficit in Ulanqab during the latest 50 years[J]. Journal of Arid Land Resources and Environment, 2019, 33(12):145-151. ]
[24]	Liu H J, Li Y, Josef T, et al. Quantitative estimation of climate change effects on potential evapotranspiration in Beijing during 1951—2010[J]. Journal of Geographical Sciences, 2014, 24(1):93-112. doi: 10.1007/s11442-014-1075-5
[25]	Jung J. Spatial analysis of the vulnerability to meteorological hazards in Korea[J]. Journal of Climate Research, 2018, 13(3):211-229. doi: 10.14383/cri.
[26]	赵峰, 毕硕本, 李兴宇, 等. 基于EOF和REOF的1470—1911年黄河中下游地区旱涝空间分布特征分析[J]. 干旱区地理, 2019, 42(4):799-809.
	[ Zhao Feng, Bi Shuoben, Li Xingyu, et al. Spatial characteristics of drought/flood disasters based on EOF and REOF in the middle and lower reaches of the Yellow River[J]. Arid Land Geography, 2019, 42(4):799-809. ]
[27]	Cheng M L, Shi G J, Xiang M Y. On the improvement of the parameter estimation of the grey model GM(1, 1) and model application[J]. Communications in Statistics-Simulation and Computation, 2020, 49(5):1367-1384. doi: 10.1080/03610918.2018.1498890
[28]	郭建平, 陈玥熤, 赵俊芳. 新疆棉花热量指数的灰色预测方法[J]. 干旱区地理, 2010, 33(5):710-715.
	[ Guo Jianping, Chen Yueyi, Zhao Junfang. Grey forecasting model of heat index of cotton in Xinjiang[J]. Arid Land Geography, 2010, 33(5):710-715. ]
[29]	张核真, 尼玛吉, 多吉次仁. 近50年西藏最长连续无降水日数变化特征[J]. 中国农学通报, 2016, 32(35):151-154.
	[ Zhang Hezhen, Ni Maji, Duoji Ciren. Variation characteristics of the longest continuous no-precipitation days in Tibet in recent 50 years[J]. Chinese Agricultural Science Bulletin, 2016, 32(35):151-154. ]
[30]	王娜. 对构建西藏生态安全屏障的几点思考[J]. 西藏发展论坛, 2011(3):43-46.
	[ Wang Na. Some thoughts on the construction of ecological security barrier in Tibet[J]. The Theoretical Platform of Tibetan Development, 2011(3):43-46. ]
[31]	史战红, 刘敏, 牛雪娜. 基于灰色预测的甘南农牧民收入趋势分析[J]. 甘肃科学学报, 2019, 31(6):8-11.
	[ Shi Zhanhong, Liu Min, Niu Xuena. Trend analysis of incomes and herdsmen in Gannan Tibetan Autonomous Prefecture based on grey prediction[J]. Journal of Gansu Sciences, 2019, 31(6):8-11. ]
[32]	赵俊芳, 郭建平, 房世波, 等. 未来气候情景下西藏地区的干湿状况变化趋势[J]. 中国农业气象, 2011, 32(1):61-66.
	[ Zhao Junfang, Guo Jianping, Fang Shibo, et al. Trends of Tibet’s dry-wet condition under future climate scenario[J]. Chinese Journal of Agrometeorology, 2011, 32(1):61-66. ]
[33]	曹雯, 申双和, 段春锋. 中国西北潜在蒸散时空演变特征及其定量化成因[J]. 生态学报, 2012, 32(11):3394-3403.
	[ Cao Wen, Shen Shuanghe, Duan Chunfeng. Temporal-spatial variations of potential evapotranspiration and quantification of the causes in northwest China[J]. Acta Ecologica Sinica, 2012, 32(11):3394-3403. ]
[34]	卓嘎, 尼玛央珍, 唐小萍. 1980—2009年西藏西北部潜在蒸散时空分布特征及其影响因素[J]. 干旱区研究, 2016, 33(4):698-707.
	[ Zhuo Ga, Nima Yangzhen, Tang Xiaoping. Spatiotemporal distribution of potential evapotranspiration and its influencing factors in northwest Tibet from 1980 to 2009[J]. Arid Zone Research, 2016, 33(4):698-707. ]